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Related papers: Identifying Ketamine Responses in Treatment-Resist…

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The glutamatergic modulator ketamine has been shown to rapidly reduce depressive symptoms in patients with treatment-resistant major depressive disorder (TRD). Although its mechanisms of action are not fully understood, changes in cortical…

Quantitative Methods · Quantitative Biology 2021-02-08 Erik D. Fagerholm , Robert Leech , Steven Williams , Carlos A. Zarate , Rosalyn J. Moran , Jessica R. Gilbert

Electroencephalogram (EEG) provides noninvasive measures of brain activity and is found to be valuable for diagnosis of some chronic disorders. Specifically, pre-treatment EEG signals in alpha and theta frequency bands have demonstrated…

Applications · Statistics 2023-05-24 Bin Yang , Xingche Guo , Ji Meng Loh , Qinxia Wang , Yuanjia Wang

There is mounting evidence of a link between the properties of electroencephalograms (EEGs) of depressive patients and the outcome of pharmacotherapy. The goal of this study was to develop an EEG biomarker of antidepressant treatment…

Neurons and Cognition · Quantitative Biology 2017-02-17 Wojciech Jernajczyk , Pawel Gosek , Miroslaw Latka , Klaudia Kozlowska , Lukasz Swiecicki , Bruce J. West

The Early diagnosis and treatment of depression is essential for effective treatment. Depression, while being one of the most common mental illnesses, is still poorly understood in both research and clinical practice. Among different…

Signal Processing · Electrical Eng. & Systems 2023-03-13 Abdolkarim Saeedi , Arash Maghsoudi , Fereidoun Nowshiravan Rahatabad

In universal environment, a patient-friendly inexpensive method is needed to realize the early diagnosis of depression, which is believed to be an effective way to reduce the mortality of depression. The purpose of this study is only to…

Signal Processing · Electrical Eng. & Systems 2020-02-28 Qiuxia Shi , Ang Liu , Rongyan Chen , Jian Shen , Qinglin Zhao , Bin Hu

Biomarkers of Major Depressive Disorder(MDD), its phases and forms have long been sought. Research indicates that the complexity measures of the cortical electrical activity (EEG) might be candidates for this role. To examine whether the…

Neurons and Cognition · Quantitative Biology 2019-12-19 Čukić Milena , Stokić Miodrag , Radenković Slavoljub , Ljubisavljević Miloš , Simić Slobodan , Danka Savić

Depression is a public health issue which severely affects one's well being and cause negative social and economic effect for society. To rise awareness of these problems, this publication aims to determine if long lasting effects of…

Machine Learning · Computer Science 2022-02-09 Egils Avots , Klavs Jermakovs , Maie Bachmann , Laura Paeske , Cagri Ozcinar , Gholamreza Anbarjafari

Depression is a widespread mental health disorder, yet its automatic detection remains challenging. Prior work has explored unimodal and multimodal approaches, with multimodal systems showing promise by leveraging complementary signals.…

Artificial Intelligence · Computer Science 2026-03-24 Annisaa Fitri Nurfidausi , Eleonora Mancini , Paolo Torroni

Running title: Frontoparietal anodal tDCS reduces ketamine-induced oscillopathies.Abstract: During the prodromal phase of schizophrenia with its complex and insidious clinical picture, electroencephalographic recordings detect widespread…

Neurons and Cognition · Quantitative Biology 2020-10-14 Caroline Lahogue , Didier Pinault

Background: In patients with psychotic disorders, sleep spindles are reduced, supporting the hypothesis that the thalamus and glutamate receptors play a crucial etio-pathophysiological role, whose underlying mechanisms remain unknown. We…

Neurons and Cognition · Quantitative Biology 2020-05-05 Didier Pinault

Anesthetic agents are known to induce a range of alterations in cortical electrophysiological activity, such as the rise of signature patterns, changes in statistical properties, and altered dynamic behavior of neural records. Plenty of…

Neurons and Cognition · Quantitative Biology 2023-09-06 Eduardo Cocca Padovani

In this paper, we aimed at reviewing present literature on employing nonlinear analysis in combination with machine learning methods, in depression detection or prediction task. We are focusing on an affordable data-driven approach,…

Signal Processing · Electrical Eng. & Systems 2019-09-10 Milena Čukić Radenković , Victoria Lopez Lopez

Depression disorder is a serious health condition that has affected the lives of millions of people around the world. Diagnosis of depression is a challenging practice that relies heavily on subjective studies and, in most cases, suffers…

Signal Processing · Electrical Eng. & Systems 2025-03-26 Amir Nassibi , Christos Papavassiliou , Ildar Rakhmatulin , Danilo Mandic , S. Farokh Atashzar

In this paper, we aimed at reviewing several different approaches present today in the search for more accurate diagnostic and treatment management in mental healthcare. Our focus is on mood disorders, and in particular on the major…

Neurons and Cognition · Quantitative Biology 2019-03-28 Milena Cukic Radenkovic

Recently, we reported an emotion self-regulation study (Zotev et al., 2020), in which patients with major depressive disorder (MDD) used simultaneous real-time fMRI and EEG neurofeedback (rtfMRI-EEG-nf) to upregulate two fMRI and two EEG…

Neurons and Cognition · Quantitative Biology 2020-10-23 Vadim Zotev , Jerzy Bodurka

This study investigates the detection and classification of depressive and non-depressive states using deep learning approaches. Depression is a prevalent mental health disorder that substantially affects quality of life, and early…

Quantitative Methods · Quantitative Biology 2026-01-19 Mohammad Reza Yousefi , Hajar Ismail Al-Tamimi , Amin Dehghani

Reliable diagnosis of depressive disorder is essential for both optimal treatment and prevention of fatal outcomes. In this study, we aimed to elucidate the effectiveness of two non-linear measures, Higuchi Fractal Dimension (HFD) and…

In current medical practice, patients undergoing depression treatment must wait four to six weeks before a clinician can assess medication response due to the delayed noticeable effects of antidepressants. Identification of a treatment…

Machine Learning · Computer Science 2025-01-09 Melanija Kraljevska , Katerina Hlavackova-Schindler , Lukas Miklautz , Claudia Plant

The detection of Alzheimers disease (AD) is considered crucial, as timely intervention can improve patient outcomes. Electroencephalogram (EEG)-based diagnosis has been recognized as a non-invasive, accessible, and cost-effective approach…

Objective Accurate identification of hypoxic-ischemic brain injury in the early neonatal period is essential for initiating therapeutic hypothermia (TH) within 6 hours of birth to optimize neurodevelopmental outcomes. We aimed to develop a…

Neurons and Cognition · Quantitative Biology 2025-11-19 Marc Fiammante , Anne-Isabelle Vermersch , Marie Vidailhet , Mario Chavez
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